Notes
Trenton Pulsipher
9/20/2018
Observations/Thoughts
Mission President Effect
New Investigators
Clearly a mission president effect is observed, note the color changes and regression lines by mission president for each mission.
However we should confirm that the mission president effect isn’t overly influenced/confounded by the number of missionaries. The plot below confirms that the mission president has a potentially strong effect on the number of new investigators within a mission.
Baptisms/Confirmations
Again a mission president effect is observed.
Sacrament Meeting Attendance
While I was skeptical of any mission president effect on sacrament meeting attendance it appears such an effect is real.
Data Cleaning/Correcting Opportunities
Potential Outliers
Outliers are possible and we would want to be careful about their effect on predictions/goals. Outliers I noticed include:
- Mission Q has one week where Baptisms/Confirmations spike to 75 when the next highest week was 16. (Maybe the 75 is supposed to be 15?) Because this field can be verified (compare MSR’s number to any self-reported numbers) I would hesitate to change it here.
- Mission K has an abnormal spike in New Investigators (1137 on 2010-02-11, note the next highest week was 428). This may be real, but if concerned about it’s effect on modeling or otherwise I would consider replacing it with the mean or the previous week’s value.
- Mission J recorded one week where sacrament meeting attendance was
raw %>% filter(mission_name == "J") %>% pull(sa_reported) %>% max()when a typical week would be 116. Again it may be worth a quick call or email to the mission president to confirm the blessed nature of such an event.
Visualizations
Trelliscope
Like Tableau, trelliscope is one R package that enables the viewer to interact visually with the data. Because trelliscope is built for use in R, we can leverage other important tools to mimic Tableau’s interactivity and go well beyond Tableau’s limits by moving visually through various slices of the data using features (cognostics) derived directly from the data. The example below should help illustrate the advantages of such an approach, thus enabling the viewer to observe the data in ways they can’t easily reach using other BI tools, like Tableau.